The Childhood Cancer Data Initiative: Using the Power of Data to Learn From and Improve Outcomes for Every Child and Young Adult With Pediatric Cancer.

Data-driven basic, translational, and clinical research has resulted in improved outcomes for children, adolescents, and young adults (AYAs) with pediatric cancers. However, challenges in sharing data between institutions, particularly in research, prevent addressing substantial unmet needs in children and AYA patients diagnosed with certain pediatric cancers. Systematically collecting and sharing data from every child and AYA can enable greater understanding of pediatric cancers, improve survivorship, and accelerate development of new and more effective therapies. To accomplish this goal, the Childhood Cancer Data Initiative (CCDI) was launched in 2019 at the National Cancer Institute. CCDI is a collaborative community endeavor supported by a 10-year, $50-million (in US dollars) annual federal investment. CCDI aims to learn from every patient diagnosed with a pediatric cancer by designing and building a data ecosystem that facilitates data collection, sharing, and analysis for researchers, clinicians, and patients across the cancer community. For example, CCDI's Molecular Characterization Initiative provides comprehensive clinical molecular characterization for children and AYAs with newly diagnosed cancers. Through these efforts, the CCDI strives to provide clinical benefit to patients and improvements in diagnosis and care through data-focused research support and to build expandable, sustainable data resources and workflows to advance research well past the planned 10 years of the initiative. Importantly, if CCDI demonstrates the success of this model for pediatric cancers, similar approaches can be applied to adults, transforming both clinical research and treatment to improve outcomes for all patients with cancer.

Topical therapy for regression and melanoma prevention of congenital giant nevi.

Giant congenital melanocytic nevi are NRAS-driven proliferations that may cover up to 80% of the body surface. Their most dangerous consequence is progression to melanoma. This risk often triggers preemptive extensive surgical excisions in childhood, producing severe lifelong challenges. We have presented preclinical models, including multiple genetically engineered mice and xenografted human lesions, which enabled testing locally applied pharmacologic agents to avoid surgery. The murine models permitted the identification of proliferative versus senescent nevus phases and treatments targeting both. These nevi recapitulated the histologic and molecular features of human giant congenital nevi, including the risk of melanoma transformation. Cutaneously delivered MEK, PI3K, and c-KIT inhibitors or proinflammatory squaric acid dibutylester (SADBE) achieved major regressions. SADBE triggered innate immunity that ablated detectable nevocytes, fully prevented melanoma, and regressed human giant nevus xenografts. These findings reveal nevus mechanistic vulnerabilities and suggest opportunities for topical interventions that may alter the therapeutic options for children with congenital giant nevi.

A Trans-Governmental Collaboration to Independently Evaluate SARS-CoV-2 Serology Assays.

The emergence of SARS-CoV-2 created a crucial need for serology assays to detect anti-SARS-CoV-2 antibodies, which led to many serology assays entering the market. A trans-government collaboration was created in April 2020 to independently evaluate the performance of commercial SARS-CoV-2 serology assays and help inform U.S. Food and Drug Administration (FDA) regulatory decisions. To assess assay performance, three evaluation panels with similar antibody titer distributions were assembled. Each panel consisted of 110 samples with positive (n = 30) serum samples with a wide range of anti-SARS-CoV-2 antibody titers and negative (n = 80) plasma and/or serum samples that were collected before the start of the COVID-19 pandemic. Each sample was characterized for anti-SARS-CoV-2 antibodies against the spike protein using enzyme-linked immunosorbent assays (ELISA). Samples were selected for the panel when there was agreement on seropositivity by laboratories at National Cancer Institute's Frederick National Laboratory for Cancer Research (NCI-FNLCR) and Centers for Disease Control and Prevention (CDC). The sensitivity and specificity of each assay were assessed to determine Emergency Use Authorization (EUA) suitability. As of January 8, 2021, results from 91 evaluations were made publicly available (https://open.fda.gov/apis/device/covid19serology/, and https://www.cdc.gov/coronavirus/2019-ncov/covid-data/serology-surveillance/serology-test-evaluation.html). Sensitivity ranged from 27% to 100% for IgG (n = 81), from 10% to 100% for IgM (n = 74), and from 73% to 100% for total or pan-immunoglobulins (n = 5). The combined specificity ranged from 58% to 100% (n = 91). Approximately one-third (n = 27) of the assays evaluated are now authorized by FDA for emergency use. This collaboration established a framework for assay performance evaluation that could be used for future outbreaks and could serve as a model for other technologies. IMPORTANCE The SARS-CoV-2 pandemic created a crucial need for accurate serology assays to evaluate seroprevalence and antiviral immune responses. The initial flood of serology assays entering the market with inadequate performance emphasized the need for independent evaluation of commercial SARS-CoV-2 antibody assays using performance evaluation panels to determine suitability for use under EUA. Through a government-wide collaborative network, 91 commercial SARS-CoV-2 serology assay evaluations were performed. Three evaluation panels with similar overall antibody titer distributions were assembled to evaluate performance. Nearly one-third of the assays evaluated met acceptable performance recommendations, and two assays had EUAs revoked and were removed from the U.S. market based on inadequate performance. Data for all serology assays evaluated are available at the FDA and CDC websites (https://open.fda.gov/apis/device/covid19serology/, and https://www.cdc.gov/coronavirus/2019-ncov/covid-data/serology-surveillance/serology-test-evaluation.html).

Cancer Informatics for Cancer Centers: Scientific Drivers for Informatics, Data Science, and Care in Pediatric, Adolescent, and Young Adult Cancer.

Cancer Informatics for Cancer Centers (CI4CC) is a grassroots, nonprofit 501c3 organization intended to provide a focused national forum for engagement of senior cancer informatics leaders, primarily aimed at academic cancer centers anywhere in the world but with a special emphasis on the 70 National Cancer Institute-funded cancer centers. This consortium has regularly held topic-focused biannual face-to-face symposiums. These meetings are a place to review cancer informatics and data science priorities and initiatives, providing a forum for discussion of the strategic and pragmatic issues that we faced at our respective institutions and cancer centers. Here, we provide meeting highlights from the latest CI4CC Symposium, which was delayed from its original April 2020 schedule because of the COVID-19 pandemic and held virtually over three days (September 24, October 1, and October 8) in the fall of 2020. In addition to the content presented, we found that holding this event virtually once a week for 6 hours was a great way to keep the kind of deep engagement that a face-to-face meeting engenders. This is the second such publication of CI4CC Symposium highlights, the first covering the meeting that took place in Napa, California, from October 14-16, 2019. We conclude with some thoughts about using data science to learn from every child with cancer, focusing on emerging activities of the National Cancer Institute's Childhood Cancer Data Initiative.

The potential of AI in cancer care and research.

Current applications of artificial intelligence (AI), machine learning, and deep learning in cancer research and clinical care are highly diverse-from aiding radiologists in reading medical images to predicting oncoprotein folding and dynamics. The list of available AI-based tools is growing rapidly and will only continue to expand. With the immense potential for AI to advance cancer research and clinical care, the National Cancer Institute (NCI) has a responsibility to consider and support the development and evaluation of such technologies. NCI's current involvement in AI research spans the spectrum of development, implementation, and assessment. That includes generating large, publicly available, curated datasets; shifting the culture of data sharing; training the next generation of scientists in both AI and cancer sciences; fostering interdisciplinary collaborations; investing in research to improve AI methods and models that are designed specifically for cancer; widening access to computing power; procuring computer architecture for future developments; and assuring AI research and technologies follow ethical principles. In addition to a broad overview of AI applications in cancer research and care, and NCI's ongoing AI-based activities, this Perspective outlines NCI's four priority areas for future investment of cancer-focused AI development.

Therapy-Induced Senescence: Opportunities to Improve Anticancer Therapy.

Cellular senescence is an essential tumor suppressive mechanism that prevents the propagation of oncogenically activated, genetically unstable, and/or damaged cells. Induction of tumor cell senescence is also one of the underlying mechanisms by which cancer therapies exert antitumor activity. However, an increasing body of evidence from preclinical studies demonstrates that radiation and chemotherapy cause accumulation of senescent cells (SnCs) both in tumor and normal tissue. SnCs in tumors can, paradoxically, promote tumor relapse, metastasis, and resistance to therapy, in part, through expression of the senescence-associated secretory phenotype. In addition, SnCs in normal tissue can contribute to certain radiation- and chemotherapy-induced side effects. Because of its multiple roles, cellular senescence could serve as an important target in the fight against cancer. This commentary provides a summary of the discussion at the National Cancer Institute Workshop on Radiation, Senescence, and Cancer (August 10-11, 2020, National Cancer Institute, Bethesda, MD) regarding the current status of senescence research, heterogeneity of therapy-induced senescence, current status of senotherapeutics and molecular biomarkers, a concept of "one-two punch" cancer therapy (consisting of therapeutics to induce tumor cell senescence followed by selective clearance of SnCs), and its integration with personalized adaptive tumor therapy. It also identifies key knowledge gaps and outlines future directions in this emerging field to improve treatment outcomes for cancer patients.

Cancer Grand Challenges: Embarking on a New Era of Discovery.

Cancer Grand Challenges is a unique funding platform that dares global, multidisciplinary teams of researchers to come together, think differently, and tackle some of the toughest challenges in cancer research. Here, we discuss the nine intractable challenges currently open for application.

Cells exhibiting strong p16INK4a promoter activation in vivo display features of senescence.

The activation of cellular senescence throughout the lifespan promotes tumor suppression, whereas the persistence of senescent cells contributes to aspects of aging. This theory has been limited, however, by an inability to identify and isolate individual senescent cells within an intact organism. Toward that end, we generated a murine reporter strain by "knocking-in" a fluorochrome, tandem-dimer Tomato (tdTom), into exon 1α of the p16INK4a locus. We used this allele (p16tdTom ) for the enumeration, isolation, and characterization of individual p16INK4a -expressing cells (tdTom+). The half-life of the knocked-in transcript was shorter than that of the endogenous p16INK4a mRNA, and therefore reporter expression better correlated with p16INK4a promoter activation than p16INK4a transcript abundance. The frequency of tdTom+ cells increased with serial passage in cultured murine embryo fibroblasts from p16tdTom/+ mice. In adult mice, tdTom+ cells could be readily detected at low frequency in many tissues, and the frequency of these cells increased with aging. Using an in vivo model of peritoneal inflammation, we compared the phenotype of cells with or without activation of p16INK4a and found that tdTom+ macrophages exhibited some features of senescence, including reduced proliferation, senescence-associated ß-galactosidase (SA-ß-gal) activation, and increased mRNA expression of a subset of transcripts encoding factors involved in SA-secretory phenotype (SASP). These results indicate that cells harboring activation of the p16INK4a promoter accumulate with aging and inflammation in vivo, and display characteristics of senescence.

Expression of p16INK4a is a biomarker of chondrocyte aging but does not cause osteoarthritis.

Cellular senescence drives a functional decline of numerous tissues with aging by limiting regenerative proliferation and/or by producing pro-inflammatory molecules known as the senescence-associated secretory phenotype (SASP). The senescence biomarker p16INK4a is a potent inhibitor of the cell cycle but is not essential for SASP production. Thus, it is unclear whether p16INK4a identifies senescence in hyporeplicative cells such as articular chondrocytes and whether p16INK4a contributes to pathologic characteristics of cartilage aging. To address these questions, we examined the role of p16INK4a in murine and human models of chondrocyte aging. We observed that p16INK4a mRNA expression was significantly upregulated with chronological aging in murine cartilage (~50-fold from 4 to 18 months of age) and in primary human chondrocytes from 57 cadaveric donors (r2  = .27, p < .0001). Human chondrocytes exhibited substantial replicative potential in vitro that depended on the activity of cyclin-dependent kinases 4 or 6 (CDK4/6), and proliferation was reduced in cells from older donors with increased p16INK4a expression. Moreover, increased chondrocyte p16INK4a expression correlated with several SASP transcripts. Despite the relationship between p16INK4a expression and these features of senescence, somatic inactivation of p16INK4a in chondrocytes of adult mice did not mitigate SASP expression and did not alter the rate of osteoarthritis (OA) with physiological aging or after destabilization of the medial meniscus. These results establish that p16INK4a expression is a biomarker of dysfunctional chondrocytes, but that the effects of chondrocyte senescence on OA are more likely driven by production of SASP molecules than by loss of chondrocyte replicative function.

The Prognostic Significance of Low-Frequency Somatic Mutations in Metastatic Cutaneous Melanoma.

Background: Little is known about the prognostic significance of somatically mutated genes in metastatic melanoma (MM). We have employed a combined clinical and bioinformatics approach on tumor samples from cutaneous melanoma (SKCM) as part of The Cancer Genome Atlas project (TCGA) to identify mutated genes with potential clinical relevance. Methods: After limiting our DNA sequencing analysis to MM samples (n = 356) and to the CANCER CENSUS gene list, we filtered out mutations with low functional significance (snpEFF). We performed Cox analysis on 53 genes that were mutated in ≥3% of samples, and had ≥50% difference in incidence of mutations in deceased subjects versus alive subjects. Results: Four genes were potentially prognostic [RAC1, FGFR1, CARD11, CIITA; false discovery rate (FDR) < 0.2]. We identified 18 additional genes (e.g., SPEN, PDGFRB, GNAS, MAP2K1, EGFR, TSC2) that were less likely to have prognostic value (FDR < 0.4). Most somatic mutations in these 22 genes were infrequent (< 10%), associated with high somatic mutation burden, and were evenly distributed across all exons, except for RAC1 and MAP2K1. Mutations in only 9 of these 22 genes were also identified by RNA sequencing in >75% of the samples that exhibited corresponding DNA mutations. The low frequency, UV signature type and RNA expression of the 22 genes in MM samples were confirmed in a separate multi-institution validation cohort (n = 413). An underpowered analysis within a subset of this validation cohort with available patient follow-up (n = 224) showed that somatic mutations in SPEN and RAC1 reached borderline prognostic significance [log-rank favorable (p = 0.09) and adverse (p = 0.07), respectively]. Somatic mutations in SPEN, and to a lesser extent RAC1, were not associated with definite gene copy number or RNA expression alterations. High (>2+) nuclear plus cytoplasmic expression intensity for SPEN was associated with longer melanoma-specific overall survival (OS) compared to lower (≤ 2+) nuclear intensity (p = 0.048). We conclude that expressed somatic mutations in infrequently mutated genes beyond the well-characterized ones (e.g., BRAF, RAS, CDKN2A, PTEN, TP53), such as RAC1 and SPEN, may have prognostic significance in MM.